FORECAST.ETS.SEASONALITY function

Returns the length of the repetitive pattern Excel detects for the specified time series.
FORECAST.ETS.Seasonality can be used following FORECAST.ETS to identify which automatic seasonality was detected and used in FORECAST.ETS.
While it can also be used independently of FORECAST.ETS, the functions are tied since the seasonality detected in this function is identical to the one used by FORECAST.ETS, considering the same input parameters that affect data completion.

Syntax

The FORECAST.ETS.SEASONALITY function syntax has the following arguments:

Values Required. Values are the historical values, for which you want to forecast the next points.

Timeline Required. The independent array or range of numeric data. The dates in the timeline must have a consistent step between them and can’t be zero.
The timeline isn't required to be sorted, as FORECAST.ETS.SEASONALITY will sort it implicitly for calculations.
If a constant step can't be identified in the provided timeline, FORECAST.ETS.SEASONALITY will return the #NUM! error.
If timeline contains duplicate values, FORECAST.ETS.SEASONALITY will return the #VALUE! error.
If the ranges of the timeline and values aren't of same size, FORECAST.ETS.SEASONALITY will return the #N/A error.

Data completion Optional. Although the timeline requires a constant step between data points, FORECAST.ETS.SEASONALITY supports up to 30% missing data, and will automatically adjust for it.
0 will indicate the algorithm to account for missing points as zeros.
The default value of 1 will account for missing points by completing them to be the average of the neighboring points.

Aggregation Optional. Although the timeline requires a constant step between data points, FORECAST.ETS.SEASONALITY will aggregate multiple points which have the same time stamp. The aggregation parameter is a numeric value indicating which method will be used to aggregate several values with the same time stamp. The default value of 0 will use AVERAGE, while other options are SUM, COUNT, COUNTA, MIN, MAX, MEDIAN.